Managing Uncertainties Due to Limited Evidence in Economic Evaluations of Novel Anti-Tuberculosis Regimens: A Systematic Review

Abstract

Background: Limited evidence for the implementation of new health technologies in low- and middle-income countries (LMICs) may lead to uncertainties in economic evaluations and cause the evaluations to produce inaccurate information for decision making. We performed a systematic review of economic evaluations on implementing new short-course regimens (SCR) for drug-sensitive and drug-resistant tuberculosis (TB), to explore how uncertainties due to the limited evidence in the studies were dealt with and to identify useful information for decision making from these studies. Methods: We searched in electronic databases PubMed, EMBASE, NHSEED, and CEA registry for economic evaluations addressing the implementation of new anti-TB SCRs in LMICs published until September 2018. We included studies addressing both the cost and outcomes of implementing a new regimen for drug-sensitive and drug-resistant TB with a shorter treatment duration than the currently used regimens. The quality of the included studies was assessed using The Consensus Health Economic Criteria checklist. We extracted information from the included studies on uncertainties and how they were managed. The management of uncertainties was compared with approaches used in early health technology assessments (HTAs), including sensitivity analyses and pragmatic scenario analyses. We extracted information that could be useful for decision making such as cost-effectiveness conclusions, and barriers to implementing the intervention. Results: Four of the 322 studies found in the search met the eligibility criteria. Three studies were model-based studies that investigated the cost effectiveness of a new first-line SCR. One study was an empirical study investigating the cost effectiveness of new regimens for drug-resistant TB. The model-based studies addressed uncertainties due to limited evidence through various sensitivity analyses as in early HTAs. They performed a deterministic sensitivity analysis and found the main drivers of the cost-effectiveness outcomes, that is, the rate of treatment default and treatment delivery costs. Additionally, two of the model-based studies performed a pragmatic scenario analysis and found a potential barrier to implementing the new first-line SCR, that is, a weak health system with a low TB care utilization rate. The empirical study only performed a few scenario analyses with different regimen prices and volumes of TB care utilization. Therefore, the study could only provide information on the main cost drivers. Conclusion: Using an approach similar to that used in early HTAs, where uncertainties due to the limited evidence are rigorously explored upfront, the economic evaluations could inform not only the decision to implement the intervention but also how to manage risks and implementation barriers.